Dr Yipeng Qin
Lecturer
Yr Ysgol Cyfrifiadureg a Gwybodeg
- qiny16@cardiff.ac.uk
- +44 (0)29 2087 5537
- 2.20, Abacws, Ffordd Senghennydd, Cathays, Caerdydd, CF24 4AG
- Ar gael fel goruchwyliwr ôl-raddedig
Trosolwg
I am a lecturer in the School of Computer Science and Informatics, and a member of the Visual Computing research group.
My research interests span three active areas in computer science: visual computing (computer graphics and computer vision), geometry processing and machine learning. Recently, I'm working on understanding the training dynamics of deep neural networks (with an emphasis on Generative Adversarial Networks) and expanding their applications in visual computing.
Please see my personal webpage for more information.
Bywgraffiad
Education and Qualifications
- 2017: PhD in Computer Science, National Centre for Computer Animation, Bournemouth University, UK
- 2013: BEng in Electrical Engineering, Shanghai Jiao Tong University, China
Career overview
- 2019 - present: Lecturer, Cardiff University, UK
- 2017 - 2019: Postdoctoral Research Fellow, Visual Computing Center, King Abdullah University of Science and Technology, Saudi Arabia
Aelodaethau proffesiynol
Member of ACM SIGGRAPH, Computer Vision Foundation (CVF)
Safleoedd academaidd blaenorol
- 2019 - present: Lecturer, Cardiff University, UK
- 2017 - 2019: Postdoctoral Research Fellow, Visual Computing Center, King Abdullah University of Science and Technology, Saudi Arabia
Pwyllgorau ac adolygu
- Journal Reviewer: IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), ACM Transactions on Graphics (TOG), IEEE Transactions on Visualization and Computer Graphics (TVCG), Computer Graphics Forum (CGF), Neurocomputing
- Conference Reviewer: ACM SIGGRAPH, ACM SIGGRAPH Asia, NeurIPS, ICLR, AAAI, Eurographics, BMVC, CVM, IJCNN
- Grant Reviewer: EPSRC
Cyhoeddiadau
2022
- Poudevigne-Durance, T., Jones, O. D. and Qin, Y. 2022. MaWGAN: a generative adversarial network to create synthetic data from datasets with missing data. Electronics 11(6), article number: 837. (10.3390/electronics11060837)
- Yan, Z., Wu, Y., Li, G., Qin, Y., Han, X. and Cui, S. 2022. Multi-level consistency learning for semi-supervised domain adaptation. Presented at: 31st International Joint Conference on Artificial Intelligence (IJCAI-ECAI 2022), Vienna, Austria, 23-29 July 2022.
- Liang, Y., Wu, J., Lai, Y. and Qin, Y. 2022. Exploring and exploiting hubness priors for high-quality GAN latent sampling. Presented at: The 39th International Conference on Machine Learning (ICML 2022), Baltimore, Maryland USA, 17-23 July 2022, Vol. 162.
- Chen, C., Shi, X., Qin, Y., Li, X., Yang, T., Han, X. and Guo, S. 2022. Real-world blind super-resolution via feature matching with implicit high-resolution priors. Presented at: the 30th ACM International Conference on Multimedia (ACMMM 2022), Lisbon, Portugal, 10 - 14 October 2022Proceedings of the 30th ACM International Conference on Multimedia (ACMMM 2022). ACM
- Yu, X., Tang, J., Qin, Y., Li, C., Han, X., Bao, L. and Cui, S. 2022. PVSeRF: joint pixel-, voxel- and surface-aligned radiance field for single-image novel view synthesis. Presented at: 30th ACM International Conference on Multimedia (ACMMM 2022), Lisbon, Portugal, 10 - 14 October 2022Proceedings ACMMM 2022 : 30th ACM International Conference on Multimedia. New York: ACM, (10.1145/3503161.3547893)
- Zhao, G., Li, G., Qin, Y., Liu, F. and Yu, Y. 2022. Centrality and consistency: two-stage clean samples identification for learning with instance-dependent noisy labels. Presented at: European Conference on Computer Vision (ECCV 2022), Tel Aviv, Israel, 23-27 October 2022.
2021
- Yan, Z., Yu, X., Qin, Y., Wu, Y., Han, X. and Cui, S. 2021. Pixel-level intra-domain adaptation for semantic segmentation. Presented at: ACM Multimedia 2021, Chengdu, China, 20-24 October 2021MM '21: Proceedings of the 29th ACM International Conference on Multimedia. ACM pp. 404-413., (10.1145/3474085.3475174)
- Zhu, Z. et al. 2021. Robust elbow angle prediction with aging soft sensors via output-level domain adaptation. IEEE Sensors Journal 21(20), pp. 22976-22984. (10.1109/JSEN.2021.3091004)
- Su, J., Gao, X., Qin, Y. and Guo, S. 2021. Correcting corrupted labels using mode dropping of ACGAN. Presented at: 15th International Symposium on Medical Information and Communication Technology (ISMICT 2021), Xiamen, China, 14-16 April 20212021 15th International Symposium on Medical Information and Communication Technology (ISMICT). IEEE pp. 98-103., (10.1109/ISMICT51748.2021.9434911)
- Chen, Z., Chen, X., Ma, Y., Guo, S., Qin, Y. and Liao, M. 2021. Human posture tracking with flexible sensors for motion recognition. Computer Animation and Virtual Worlds (10.1002/cav.1993)
2020
- Qin, Y., Mitra, N. and Wonka, P. 2020. How does Lipschitz regularization influence GAN training?. Presented at: 16th European Conference on Computer Vision (ECCV 2020), Glasgow, Scotland, 23-28 August 2020 Presented at Vevaldi, A. et al. eds.Computer Vision – ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XVI. Lecture Notes in Computer Science Springer pp. 310-326., (10.1007/978-3-030-58517-4_19)
- Abdal, R., Qin, Y. and Wonka, P. 2020. Image2StyleGAN++: how to edit the embedded images?. Presented at: Conference on Computer Vision and Pattern Recognition (CVPR 2020), Seattle, Washington, USA, 16-18 June 2020.
- Zhu, P., Abdal, R., Qin, Y. and Wonka, P. 2020. SEAN: image synthesis with semantic region-adaptive normalization. Presented at: Conference on Computer Vision and Pattern Recognition (CVPR 2020), Seattle, Washington, USA, 14-19 June 2020.
2019
- Abdal, R., Qin, Y. and Wonka, P. 2019. Image2StyleGAN: How to embed images into the styleGAN latent space?. Presented at: International Conference on Computer Vision (ICCV) 2019, Seoul, South Korea, 27 October 2019 - 3 November 2019Proceedings of the International Conference on Computer Vision (ICCV) 2019. IEEE pp. 4431-4440., (\10.1109/ICCV.2019.00453)
2017
- Qin, Y., Yu, H. and Zhang, J. 2017. Fast and memory-efficient Voronoi diagram construction on triangle meshes. Computer Graphics Forum 36(5), pp. 93-104. (10.1111/cgf.13248)
2016
- Qin, Y., Han, X., Yu, H., Yu, Y. and Zhang, J. 2016. Fast and exact discrete geodesic computation based on triangle-oriented wavefront propagation. ACM Transactions on Graphics 35(4), article number: 125. (10.1145/2897824.2925930)
2015
- Yu, H., Qin, Y. and Zhang, J. J. 2015. Eigenspace-based surface completeness. Journal of Electronic Imaging 24(2), article number: 23037. (10.1117/1.JEI.24.2.023037)
Addysgu
- 2021/22 - now, CMT307 Applied Machine Learning
- 2021/22 - now, CMT316 Applications of Machine Learning: Natural Language Processing/Computer Vision
- 2019/20 - now, CM1205 Architecture and Operating Systems, Module Lead
My research interests span three active areas in computer science: visual computing (computer graphics and computer vision), geometry processing and machine learning. Recently, I'm working on understanding the training dynamics of deep neural networks (with an emphasis on Generative Adversarial Networks) and expanding their applications in visual computing.
Supervision
I am interested in supervising PhD students in the areas of:
- AI for Generative Modelling
- Interpretable ML/AI for Visual Content Generation
- Bias and Fairness in AI
- Image Synthesis and Manipulation
- 3D Geometry Processing